Autonomous worksites are designed to provide productivity gains through more consistency in processes. Such worksites may employ a plurality of autonomous machines such as, for example, off-highway haul trucks, motor graders, and other types of heavy equipment to perform a variety of tasks. Primary operation of such machines may be controlled by a combination of on-board and off-board computers, processors, and other electronic controllers rather than human operators. As a result, autonomous operation may enhance the productivity of the machines, and reduce the human resources required for controlling the operation of the worksite.
To operate the autonomous machines safely and efficiently on the worksite, the machines are usually equipped with sensors for detecting objects on the worksite. For example, RADAR (radio detection and ranging) sensors, SONAR (sound navigation and ranging) sensors, LIDAR (light detection and ranging) sensors, IR (infrared) and non-IR cameras, and other similar sensors may be used. The sensed objects may include specific geographical features of the worksite (for example, berms, markers, rocks, etc.), the other machines on the worksite, and any obstructions on the worksite. The machines are also generally equipped with sensors for detecting information regarding characteristics of the machine itself (for example, engine speed, travel and/or work speed, steering angle, transmission gear or gear ratio, orientation such as pitch and roll, geographical location, load weight, and load distribution). A vehicle model, which is a computer model that is used in autonomous operation of the machine on the worksite, may be stored in a computer memory of the machine. Processors on-board the machine may receive outputs from the sensors and, using the vehicle model, may predict how the machine will operate, for example, given its current speed and steering angle, and/or future drive commands of the machine. In the event the processors predict that the machine should not continue on its current course (for example, the processors predict the machine will collide with a sensed object if the machine maintains its current steering angle), the processors may also use the vehicle model to determine what changes should be made, and to predict whether these changes will, in fact, result in continued safe and efficient operation of the machine.
Periodic calibration of the vehicle model is necessary for desired machine operation since the predicted performance of the autonomous machine may vary substantially from the actual performance of the machine. For example, calibration may be required due to, among other things, a change in worksite conditions, a change in the configuration of the machine, and/or because of wear of components used in the machine.
To perform calibration of the vehicle model, the autonomous machine may undergo a series of specific tests. The tests measure the actual performance of the machine, using the uncalibrated vehicle model, under a variety of conditions, including different loads, speeds, steering angles, and orientations of the machine. After the conclusion of the testing, the actual performance of the machine under the various conditions is compared to the performance that was predicted by the uncalibrated vehicle model under those same conditions. The vehicle model may then be adjusted or calibrated based on the comparison, so that future use of the calibrated vehicle model will result in the actual operation of the autonomous machine being substantially the same as the predicted operation of the machine.
An exemplary calibration system and method is described in U.S. Patent Publication No. 2006/0164295 (the '295 publication) by Focke et al. published on Jul. 27, 2006. Specifically, the '295 publication describes a system for simultaneous calibration of two different types of sensors, for example, an image sensor and a radar sensor mounted on a motor vehicle. During calibration of the two sensors, the motor vehicle is aligned in front of a calibration object in such a way that the image and radar sensors detect reference features of the calibration object and responsively create calibration data. The calibration data is used directly for calibration of the participating sensors. For example, the calibration data is used for automatic correction of a deviation of a sensor axis in relation to a vehicle longitudinal axis or by an automotive technician for mechanical adjustment of sensor placement. These procedures are possible during manufacture or repair of the motor vehicle.
Although the sensor system of the '295 publication may be helpful in calibrating machine-mounted sensors, the benefit may be limited as there are a number of different types of vehicle model calibration that may be necessary in order for an autonomous work machine to operate efficiently. For example, different loads, speeds, steering angles, and orientations of the machine may all be parameters that require calibration and/or recalibration during the lifetime of the autonomous machine.
Challenges to calibrating an autonomous work machine vehicle model may include, for example, the need for an autonomous machine to be transported to an area designated specifically for calibration-related activity. The designated area may be a significant distance from the autonomous worksite. The size of the designated area may limit the number of machines undergoing vehicle model calibration at any particular time. Further, it may take a significant amount of time to complete all of the specific tests required for complete calibration of the vehicle model. Thus, the autonomous machine may not be available to perform any task on the autonomous worksite for a relatively long period of time, until the vehicle model is completely calibrated and the autonomous machine is transported to the worksite. Subsequent recalibration of the vehicle model may result in similar disadvantages, since it may be necessary to transport the autonomous machine back to the designated area to again undergo the series of specific tests.
The disclosed systems and methods are directed to overcoming one or more of the problems set forth above and/or other problems of the prior art.